Obviously a clickbait headline, few people think current tech will lead to AGI, but while we all wait on a new breakthrough in AI, we can build much more impressive systems with what we have now than even a few years ago.
I went to a talk from people who had built more scalable training algorithms for Restricted Boltzmann Mahcines (which Hinton was a pioneer in) a few months ago and asked them why they had chosen to use RBMs. Besides the waffly answers about how generative models were more interpretable than discriminative models, the real answer seems to have been that this was a research program that had started when RBMs were still in vogue, and their funding was tied to it, and once it ran out they were going to switch to investigating Generative Adversarial Networks like everyone else.
I went to a talk from people who had built more scalable training algorithms for Restricted Boltzmann Mahcines (which Hinton was a pioneer in) a few months ago and asked them why they had chosen to use RBMs. Besides the waffly answers about how generative models were more interpretable than discriminative models, the real answer seems to have been that this was a research program that had started when RBMs were still in vogue, and their funding was tied to it, and once it ran out they were going to switch to investigating Generative Adversarial Networks like everyone else.